Search results for: Biomedical application

Authors: Larbi Belagraa

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The universal need to conserve resources, protect the environment and use energy efficiently must necessarily be felt in the field of concrete technology. The recycling of construction and demolition waste as a source of aggregates for the production of concrete has attracted growing interest from the construction industry. In Algeria, the depletion of natural deposits of aggregates and the difficulties in setting up new quarries; makes it necessary to seek new sources of supply, to meet the need for aggregates for the major projects launched by the Algerian government in the last decades. In this context, this work is a part of the approach to provide answers to concerns about the lack of aggregates for concrete. It also aims to develop the inert fraction of demolition materials and mainly concrete construction demolition waste(C&D) as a source of aggregates for the manufacture of new hydraulic concretes based on recycled aggregates. This experimental study presents the results of physical and mechanical characterizations of natural and recycled aggregates, as well as their influence on the properties of fresh and hardened concrete. The characterization of the materials used has shown that the recycled aggregates have heterogeneity, a high water absorption capacity, and a medium quality hardness. However, the limits prescribed by the standards in force do not disqualify these materials of use for application as recycled aggregate concrete type (RAC). The results obtained from the present study show that acceptable mechanical, compressive, and flexural strengths of RACs are obtained using Superplasticizer SP 45 and 5% replacement of cement with silica fume based on recycled aggregates, compared to those of natural concretes. These mechanical performances demonstrate a characteristic resistance at 28 days in compression within the limits of 30 to 40 MPa without any particular suitable technology .to be adapted in the case.

Keywords: recycled aggregates, concrete(RAC), superplasticizer, silica fume, compressive strength

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Authors: Siham Rahoui, Amr Mahfouz, Amr Arisha

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In a highly competitive environment characterised by uncertainty and disruptions, such as the recent COVID-19 outbreak, supply chains (SC) face the challenge of maintaining their cost at minimum levels while continuing to provide customers with high-quality products and services. More importantly, businesses in such an economic context strive to maintain survival by keeping the cost of undertaken activities (such as logistics) low and in-house. To do so, managers need to understand the costs associated with different products and services in order to have a clear vision of the SC performance, maintain profitability levels, and make strategic decisions. In this context, SC literature explored different costing models that sought to determine the costs of undertaking supply chain-related activities. While some cost accounting techniques have been extensively explored in the SC context, more contributions are needed to explore the potential of time driven activity-based costing (TDABC). More specifically, more applications are needed in the manufacturing context of the SC, where the debate is ongoing. The aim of the study is to assess the capability of the technique to assess the operational performance of the logistics function. Through a case study methodology applied to a manufacturing company operating in the automotive industry, TDABC evaluates the efficiency of the current configuration and its logistics processes. The study shows that monitoring the process efficiency and cost efficiency leads to strategic decisions that contributed to improve the overall efficiency of the logistics processes.

Keywords: efficiency, operational performance, supply chain costing, time driven activity based costing

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Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

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This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

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Authors: Gurlal Singh, Rupinder Singh

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The possible role of the engine brake is to convert a power-producing engine into a power-absorbing retarding mechanism. In this braking system, exhaust gas (EG) from the internal combustion (IC) engines is used to operate air brake in the automobiles. Airbrake is most used braking system in vehicles. In the proposed model, instead of air brake, EG is used to operate the brake lever and stored in a specially designed tank. This pressure of EG is used to operate the pneumatic cylinder and brake lever. Filters used to remove the impurities from the EG, then it is allowed to store in the tank. Pressure relief valve is used to achieve a specific pressure in the tank and helps to avoid further damage to the tank as well as in an engine. The petrol engine is used in the proposed EG braking system. The petrol engine is chosen initially because it produces less impurity in the exhaust than diesel engines. Moreover, exhaust brake system (EBS) for the Diesel engines is composed of gate valve, pneumatic cylinder and exhaust brake valve with the on-off solenoid. Exhaust brake valve which is core component of EBS should have characteristics such as high reliability and long life. In a diesel engine, there is butterfly valve in exhaust manifold connected with solenoid switch which is used to on and off the butterfly valve. When butterfly valve closed partially, then the pressure starts built up inside the exhaust manifold and cylinder that actually resist the movement of piston leads to crankshaft getting stops resulting stopping of the flywheel. It creates breaking effect in a diesel engine. The exhaust brake is a supplementary breaking system to the service brake. It is noted that exhaust brake increased 2-3 fold the life of service brake may be due to the creation of negative torque which retards the speed of the engine. More study may also be warranted for the best suitable design of exhaust brake in a diesel engine.

Keywords: exhaust gas, automobiles, solenoid, airbrake

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Authors: Massimiliano Frezza, Sergio Bianchi, Augusto Pianese

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Introduced by Shannon in 1948 in the field of information theory as the average rate at which information is produced by a stochastic set of data, the concept of entropy has gained much attention as a measure of uncertainty and unpredictability associated with a dynamical system, eventually depicted by a stochastic process. In particular, the Shannon entropy measures the degree of order/disorder of a given signal and provides useful information about the underlying dynamical process. It has found widespread application in a variety of fields, such as, for example, cryptography, statistical physics and finance. In this regard, many contributions have employed different measures of entropy in an attempt to characterize the financial time series in terms of market efficiency, market crashes and/or financial crises. The Shannon entropy has also been considered as a measure of the risk of a portfolio or as a tool in asset pricing. This work investigates the theoretical link between the Shannon entropy and the multifractional Brownian motion (mBm), stochastic process which recently is the focus of a renewed interest in finance as a driving model of stochastic volatility. In particular, after exploring the current state of research in this area and highlighting some of the key results and open questions that remain, we show a well-defined relationship between the Shannon (log)entropy and the memory function H(t) of the mBm. In details, we allow both the length of time series and time scale to change over analysis to study how the relation modify itself. On the one hand, applications are developed after generating surrogates of mBm trajectories based on different memory functions; on the other hand, an empirical analysis of several international stock indexes, which confirms the previous results, concludes the work.

Keywords: Shannon entropy, multifractional Brownian motion, Hurst–Holder exponent, stock indexes

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Authors: Andrea Zielke-Nadkarni

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Pain management is a question of quality of life and an indicator for nursing quality. Chronic pain which is predominant in oncology and palliative nursing situations is perceived today as a multifactorial, individual emotional experience with specific characteristics including the sociocultural dimension when dealing with migrant patients. This dimension of chronic pain is of major importance in professional nursing of migrant patients in hospices or palliative care units. Objectives of the study are: 1. To find out more about the sociocultural views on pain and nursing care, on customs and nursing practices connected with pain of both Turkish Muslim and German Christian women, 2. To improve individual and family oriented nursing practice with view to sociocultural needs of patients in severe pain in palliative care. In a qualitative-explorative comparative study 4 groups of women, Turkish Muslims immigrants (4 from the first generation, 5 from the second generation) and German Christian women of two generations (5 of each age group) of the same age groups as the Turkish women and with similar educational backgrounds were interviewed (semistructured ethnographic interviews using Spradley, 1979) on their perceptions and experiences of pain and nursing care within their families. For both target groups the presentation will demonstrate the following results in detail: Utterance of pain as well as “private” and “public” pain vary within different societies and cultures. Permitted forms of pain utterance are learned in childhood and determine attitudes and expectations in adulthood. Language, especially when metaphors and symbols are used, plays a major role for misunderstandings. The sociocultural context of illness may include specific beliefs that are important to the patients and yet seem more than far-fetched from a biomedical perspective. Pain can be an influential factor in family relationships where respect or hierarchies do not allow the direct utterance of individual needs. Specific resources are often, although not exclusively, linked to religious convictions and are significantly helpful in reducing pain. The discussion will evaluate the results of the study with view to the relevant literature and present nursing interventions and instruments beyond medication that are helpful when dealing with patients from various socio-cultural backgrounds in painful end-oflife situations.

Keywords: pain management, migrants, sociocultural context, palliative care

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Authors: Yudhajit Datta, Hamsi Iyer, Jonathan Bandi, Ankit Sethia

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Motion Tracking and Stereo Vision are complicated, albeit well-understood problems in computer vision. Existing softwares that combine the two approaches to perform stereo motion tracking typically employ complicated and computationally expensive procedures. The purpose of this study is to create a simple and effective solution capable of combining the two approaches. The study aims to explore a strategy to combine the two techniques of two-dimensional motion tracking using Kalman Filter; and depth detection of object using Stereo Vision. In conventional approaches objects in the scene of interest are observed using a single camera. However for Stereo Motion Tracking; the scene of interest is observed using video feeds from two calibrated cameras. Using two simultaneous measurements from the two cameras a calculation for the depth of the object from the plane containing the cameras is made. The approach attempts to capture the entire three-dimensional spatial information of each object at the scene and represent it through a software estimator object. In discrete intervals, the estimator tracks object motion in the plane parallel to plane containing cameras and updates the perpendicular distance value of the object from the plane containing the cameras as depth. The ability to efficiently track the motion of objects in three-dimensional space using a simplified approach could prove to be an indispensable tool in a variety of surveillance scenarios. The approach may find application from high security surveillance scenes such as premises of bank vaults, prisons or other detention facilities; to low cost applications in supermarkets and car parking lots.

Keywords: kalman filter, stereo vision, motion tracking, matlab, object tracking, camera calibration, computer vision system toolbox

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Authors: Richard Patrick Kabuye

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This study focuses on the addressing the enhancement of in-service training programs as a tool of transforming the existing traditional approaches of formal lectures/contact hours. This will be supported with a more versatile, robust, and remotely accessible means of mobile based e-learning, as a support tool for the traditional means. A combination of various factors in education and incorporation of the eLearning strategy proves to be a key factor in effective in-service education. Key factor needs to be factored in so as to maintain a credible co-existence of the programs, with the prevailing social, economic and political environments. Effective in-service education focuses on having immediate transformation of knowledge into practice for a good time period, active participation of attendees, enable before training planning, in training assessment and post training feedback training analysis which will yield knowledge to the trainers of the applicability of knowledge given out. All the above require a more robust approach to attain success in implementation. Incorporating mobile technology in eLearning will enable the above to be factored together in a more coherent manner, as it is evident that participants have to take time off their duties and attend to these training programs. Making it mobile, will save a lot of time since participants would be in position to follow certain modules while away from lecture rooms, get continuous program updates after completing the program, send feedback to instructors on knowledge gaps, and a wholly conclusive evaluation of the entire program on a learn as you work platform. This study will follow both qualitative and quantitative approaches in data collection, and this will be compounded incorporating a mobile eLearning application using Android.

Keywords: in service, training, mobile, e- learning, model

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Authors: Amira M. Othman

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Despite the massive array of literature that engages with the Egyptian legislative system on a theoretical level, very little attention has been dedicated to the comparison between the legislative clauses on the one hand, and the (absence of their) real-world implementation on the other. This paper starts with this discrepancy, focusing on the legal proceedings in some recent cases dubbed ‘political,’ in which defendants received death sentences. Then, it sheds light on the trend of practical disregard of the law on behalf of the criminal justice apparatuses (whether security forces, public prosecution offices, lawyers, judges, prison wardens, and executioners) through the examination of case files and the conduction of interviews with some defense lawyers in the cases in question. It also identifies the resultant state of confusion among prison staff, as manifest in their treatment of defendants even before the death sentences against them is pronounced; in other words, the application of some aspects of the law in certain cases, and their simultaneous disregard of others. Then, the paper explores the effects of such execution of the law on the death row inmates, as it identifies the different strategies through which defendants who are sentenced to death appropriate a number of legal clauses to their benefit, thereby embarrassing - or highly irritating - the judges that pronounce their death sentences. In addition to appropriation, other strategies include the contestation of the law and their presence before the courts in general, as well as the complete disregard and dismissal of the legal system altogether. Finally, the paper investigates the consequent conceptual effect on the first degree families of death row inmates, namely how their daily encounters with the Egyptian legislative system - particularly its emphasis on the absence of the otherwise binding local legislation - continue to shape their conceptions of the ‘law,’ of ‘justice,’ and their trust in the ‘state.’

Keywords: death penalty, Egyptian law absence, justice, political cases

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Authors: Emmanuel Chibuogu Asogwa, Tochukwu Sunday Belonwu

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An urgent demand for creative solutions has been created by the rapid expansion of medical knowledge, the complexity of patient care, and the requirement for more precise decision-making. As a solution to this problem, the creation of a Medical Intelligent Process Model (MIPM) utilizing ontology-based appears as a promising way to overcome this obstacle and unleash the full potential of healthcare systems. The development of a Medical Intelligent Process Model (MIPM) using ontology-based techniques is motivated by a lack of quick access to relevant medical information and advanced tools for treatment planning and clinical decision-making, which ontology-based techniques can provide. The aim of this work is to develop a structured and knowledge-driven framework that leverages ontology, a formal representation of domain knowledge, to enhance various aspects of healthcare. Object-Oriented Analysis and Design Methodology (OOADM) were adopted in the design of the system as we desired to build a usable and evolvable application. For effective implementation of this work, we used the following materials/methods/tools: the medical dataset for the test of our model in this work was obtained from Kaggle. The ontology-based technique was used with Confusion Matrix, MySQL, Python, Hypertext Markup Language (HTML), Hypertext Preprocessor (PHP), Cascaded Style Sheet (CSS), JavaScript, Dreamweaver, and Fireworks. According to test results on the new system using Confusion Matrix, both the accuracy and overall effectiveness of the medical intelligent process significantly improved by 20% compared to the previous system. Therefore, using the model is recommended for healthcare professionals.

Keywords: ontology-based, model, database, OOADM, healthcare

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Authors: Wajih Abbassi, Zouhaier Ben Khelifa

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The present research points towards the empirical validation of three options valuation models, the ad-hoc Black-Scholes model as proposed by Berkowitz (2001), the constant elasticity of variance model of Cox and Ross (1976) and the Kou jump-diffusion model (2002). Our empirical analysis has been conducted on a sample of 26,974 options written on three indexes, the S&P 500, Nasdaq 100 and the Russell 2000 that were negotiated during the year 2007 just before the sub-prime crisis. We start by presenting the theoretical foundations of the models of interest. Then we use the technique of trust-region-reflective algorithm to estimate the structural parameters of these models from cross-section of option prices. The empirical analysis shows the superiority of the Kou jump-diffusion model. This superiority arises from the ability of this model to portray the behavior of market participants and to be closest to the true distribution that characterizes the evolution of these indices. Indeed the double-exponential distribution covers three interesting properties that are: the leptokurtic feature, the memory less property and the psychological aspect of market participants. Numerous empirical studies have shown that markets tend to have both overreaction and under reaction over good and bad news respectively. Despite of these advantages there are not many empirical studies based on this model partly because probability distribution and option valuation formula are rather complicated. This paper is the first to have used the technique of nonlinear curve-fitting through the trust-region-reflective algorithm and cross-section options to estimate the structural parameters of the Kou jump-diffusion model.

Keywords: jump-diffusion process, Kou model, Leptokurtic feature, trust-region-reflective algorithm, US index options

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Authors: Amal A. Al-Kahlawy, Heba H. El-Maghrabi

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Due to the increasing need to environment protection in real time need to energize new materials are under extensive investigations. Between others, TiO2 nanotubes (TNTs) nanocomposite with iron oxide and silver carbonate, are promising alternatives as high-efficiency visible light photocatalyst due to their unique properties and their superior charge transport properties. Our efforts in this domain aim the construction of novel nanocomposite of TiO2NT/Fe2O3@Ag2CO3. The structure, surface morphology, chemical composition and optical properties were characterized by X-ray diffraction (XRD), Raman, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy dispersive X-ray spectrometer (EDS), transmission electron microscopy (TEM), selected area electron diffraction (SAED) and UV–vis diffuse reflectance spectroscopy (DRS). XRD results confirm the interaction of TiO2-NT with iron oxide. This novel nanocomposite shows remarkably enhanced performance for phenol compounds photodegradation. The experimental data shows a promising photocatalytic activity. In particular, a maximum value of 450 mg/g was removed within 60 min at solar light irradiation with degradation efficiency of 99.5%. The high photocatalytic activity of the nanocomposite is found to be related to the increased adsorption toward chemical species, enhanced light absorption and efficient charge separation and transfer. Finally, the designed TiO2NT/Fe2O3@Ag2CO3 nanocomposite has a great degree of sustainability and could has a potential application for the industrial treatment of wastewater containing toxic organic materials.

Keywords: nanocomposite, photocatalyst, solar energy, titanium dioxide nanotubes

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Authors: Md. Moniruzzaman, Thirayoot Limanond

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Being the most visible indicator, the transport system of a city points out how developed the city is. Dhaka megacity holds a mixed composition of motorized and non-motorized modes of transport and the number of vehicle figure is escalating over times. And this obviously poses associated environmental costs like air pollution, noise etc. which is degrading the quality of life in the city. Eventually sustainable transport or more importantly green transport from environmental point of view has become a prime choice to the transport professionals in order to cope up the crisis. Currently the city authority is planning to execute such sustainable transport systems that could serve the pressing demand of the present and meet the future needs effectively. This study focuses on the selection and evaluation of green transportation systems among potential alternatives on a priority basis. In this paper, Fuzzy TOPSIS - a multi-criteria decision method is presented to find out the most prioritized alternative. In the first step, Twenty-one individual specific criteria for sustainability assessment are selected. In the following step, experts provide linguistic ratings to the potential alternatives with respect to the selected criteria. The approach is used to generate aggregate scores for sustainability assessment and selection of the best alternative. In the third step, a sensitivity analysis is performed to understand the influence of criteria weights on the decision making process. The key strength of fuzzy TOPSIS approach is its practical applicability having a generation of good quality solution even under uncertainty.

Keywords: green transport, multi-criteria decision approach, urban transportation system, sustainability assessment, fuzzy theory, uncertainty

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Authors: Gajanan M. Sonwane

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The computational studies on 2-phenazinamines with their protein targets have been carried out to design compounds with potential anticancer activity. This strategy of designing compounds possessing selectivity over specific tyrosine kinase has been achieved through G-QSAR and molecular docking studies. The objective of this research has been to design newer 2-phenazinamine derivatives as Bcr-Abl tyrosine kinase inhibitors by G-QSAR, molecular docking studies followed by wet-lab studies along with evaluation of their anticancer potential. Computational chemistry was done by using VLife MDS 4.3 and Autodock 4.2 followed by wet-lab experiments for synthesizing 2-phenazinamine derivatives. The chemical structures of ligands in 2D were drawn by employing Chemdraw 2D Ultra 8.0 and were converted into 3D. These were optimized by using a semi-empirical method called MOPAC. The protein structure was retrieved from RCSC protein data bank as a PDB file. The binding interactions of protein and ligands were done by using PYMOL. The molecular properties of the designed compounds were predicted in silico by using Osiris property explorer. The parent compound 2-phenazinamine was synthesized by reduction of 2, 4-dinitro-N-phenyl-benzenamine in the presence of tin chloride followed by cyclization in the presence of nitrobenzene and magnesium sulfate. The derivatization at the amino function of 2-phenazinamine was performed by treating parent compound with various aldehydes in the presence of dicyclohexylcarbodiimide (DCC) and urea to afford 2-(2-chlorophenyl)-3-(phenazine-2-yl) thiazolidine-4-one. Synthesized 39 novel derivatives of 2-phenazinamine and performed antioxidant activity, anti antiproliferative on the bulb of onion and anticancer activity on cell line showing significant competition with marked blockbuster drug imatinib.

Keywords: computer-aided drug design, tyrosin kinases, anticancer, docking

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Authors: Nicholas V. Scott, Jack McCarthy

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Military, law enforcement, and counter terrorism organizations are often tasked with target detection and image characterization of scenes containing explosive materials in various types of environments where light scattering intensity is high. Mitigation of this photonic noise using classical digital filtration and signal processing can be difficult. This is partially due to the lack of robust image processing methods for photonic noise removal, which strongly influence high resolution target detection and machine learning-based pattern recognition. Such analysis is crucial to the delivery of reliable intelligence. Polarization filters are a possible method for ambient glare reduction by allowing only certain modes of the electromagnetic field to be captured, providing strong scene contrast. An experiment was carried out utilizing a polarization lens attached to a hyperspectral imagery camera for the purpose of exploring the degree to which an imaged polarized scene of potassium, phosphorus, and nitrogen mixture allows for improved target detection and image segmentation. Preliminary imagery results based on the application of machine learning algorithms, including competitive leaky learning and distance metric analysis, to polarized hyperspectral imagery, suggest that polarization filters provide a slight advantage in image segmentation. The results of this work have implications for understanding the presence of explosive material in dry, desert areas where reflective glare is a significant impediment to scene characterization.

Keywords: explosive material, hyperspectral imagery, image segmentation, machine learning, polarization

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Authors: Siti Aisya Gany, Swee Ching Tan, Sook Yee Gan

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Diminished antioxidant defense or increased production of reactive oxygen species in the biological system can result in oxidative stress which may lead to various neurodegenerative diseases including Alzheimer’s disease (AD). Microglial activation also contributes to the progression of AD by producing several pro-inflammatory cytokines, nitric oxide (NO), and prostaglandin E2 (PGE2). Oxidative stress and inflammation have been reported to be possible pathophysiological mechanisms underlying AD. In addition, the cholinergic hypothesis postulates that memory impairment in patient with AD is also associated with the deficit of cholinergic function in the brain. Although a number of drugs have been approved for the treatment of AD, most of these synthetic drugs have diverse side effects and yield relatively modest benefits. Marine algae have great potential in pharmaceutical and biomedical applications as they are valuable sources of bioactive properties such as anti-coagulation, anti-microbial, anti-oxidative, anti-cancer and anti-inflammatory. Hence, this study aimed to provide an overview of the properties of Malaysian seaweeds (Padina australis, Sargassum polycystum and Caulerpa racemosa) in inhibiting oxidative stress, neuroinflammation and cholinesterase enzymes. All tested samples significantly exhibit potent DPPH and moderate Superoxide anion radical scavenging ability (P<0.05). Hexane and methanol extracts of S. polycystum exhibited the most potent radical scavenging ability with IC50 values of 0.1572 ± 0.004 mg/ml and 0.8493 ± 0.02 for DPPH and ABTS assays, respectively. Hexane extract of C. racemosa gave the strongest superoxide radical inhibitory effect (IC50 of 0.3862± 0.01 mg/ml). Most seaweed extracts significantly inhibited the production of cytokine (IL-6, IL-1 β, TNFα) and NO in a concentration-dependent manner without causing significant cytotoxicity to the lipopolysaccharide (LPS)-stimulated microglia cells (P<0.05). All extracts suppressed cytokine and NO level by more than 80% at the concentration of 0.4mg/ml. In addition, C. racemosa and S. polycystum also showed anti-acetylcholinesterase activities with the IC50 values ranging from 0.086-0.115 mg/ml. Moreover, C. racemosa and P. australis were also found to be active against butyrylcholinesterase with IC50 values ranging from 0.118-0.287 mg/ml.

Keywords: anti-cholinesterase, anti-oxidative, neuroinflammation, seaweeds

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, gain

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Authors: J. K Adedeji, O. H Olowomofe, C. O Alo, S.T Ijatuyi

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The issue of high blood sugar level, the effects of which might end up as diabetes mellitus, is now becoming a rampant cardiovascular disorder in our community. In recent times, a lack of awareness among most people makes this disease a silent killer. The situation calls for urgency, hence the need to design a device that serves as a monitoring tool such as a wrist watch to give an alert of the danger a head of time to those living with high blood glucose, as well as to introduce a mechanism for checks and balances. The neural network architecture assumed 8-15-10 configuration with eight neurons at the input stage including a bias, 15 neurons at the hidden layer at the processing stage, and 10 neurons at the output stage indicating likely symptoms cases. The inputs are formed using the exclusive OR (XOR), with the expectation of getting an XOR output as the threshold value for diabetic symptom cases. The neural algorithm is coded in Java language with 1000 epoch runs to bring the errors into the barest minimum. The internal circuitry of the device comprises the compatible hardware requirement that matches the nature of each of the input neurons. The light emitting diodes (LED) of red, green, and yellow colors are used as the output for the neural network to show pattern recognition for severe cases, pre-hypertensive cases and normal without the traces of diabetes mellitus. The research concluded that neural network is an efficient Accu-Chek design tool for the proper monitoring of high glucose levels than the conventional methods of carrying out blood test.

Keywords: Accu-Check, diabetes, neural network, pattern recognition

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Authors: Mohammed A. Elhaj, Jamal S. Yassin

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Owing to the lack of synchronization between the solar energy availability and the heat demands in a specific application, the energy storing sub-system is necessary to maintain the continuity of thermal process. The present work is dealing with an active solar heating storing system in which an air solar collector is connected to storing unit where this energy is distributed and provided to the heated space in a controlled manner. The solar collector is a box type absorber where the air flows between a number of vanes attached between the collector absorber and the bottom plate. This design can improve the efficiency due to increasing the heat transfer area exposed to the flowing air, as well as the heat conduction through the metal vanes from the top absorbing surface. The storing unit is a packed bed type where the air is coming from the air collector and circulated through the bed in order to add/remove the energy through the charging / discharging processes, respectively. The major advantage of the packed bed storage is its high degree of thermal stratification. Numerical solution of the packed bed energy storage is considered through dividing the bed into a number of equal segments for the bed particles and solved the energy equation for each segment depending on the neighbor ones. The studied design and performance parameters in the developed simulation model including, particle size, void fraction, etc. The final results showed that the collector efficiency was fluctuated between 55%-61% in winter season (January) under the climatic conditions of Misurata in Libya. Maximum temperature of 52ºC is attained at the top of the bed while the lower one is 25ºC at the end of the charging process of hot air into the bed. This distribution can satisfy the required load for the most house heating in Libya.

Keywords: solar energy, thermal process, performance, collector, packed bed, numerical analysis, simulation

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Authors: W. A. M. Abdel Kawy, Kh. M. Darwish

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Adequate land use selection is an essential step towards achieving sustainable development. The main object of this study is to develop a new scale for land suitability system, which can be compatible with the local conditions. Furthermore, it aims to adapt the conventional land suitability systems to match the actual environmental status in term of soil types, climate and other conditions to evaluate land suitability for newly reclaimed areas. The new system suggests calculation of land suitability considering 20 factors affecting crop selection grouping into five categories; crop-agronomic, land management, development, environmental conditions and socio – economic status. Each factor is summed by each other to calculate the total points. The highest rating for each factor indicates the highest preference for the evaluated crop. The highest rated crops for each group are those with the highest points for the actual suitability. This study was conducted to assess the application efficiency of the new land suitability scale in recently reclaimed sites in Egypt. Moreover, 35 representative soil profiles were examined, and soil samples were subjected to some physical and chemical analysis. Actual and potential suitabilities were calculated by using the new land suitability scale. Finally, the obtained results confirmed the applicability of a new land suitability system to recommend the most promising crop rotation that can be applied in the study areas. The outputs of this research revealed that the integration of different aspects for modeling and adapting a proposed model provides an effective and flexible technique, which contribute to improve land suitability assessment for several crops to be more accurate and reliable.

Keywords: analytic hierarchy process, land suitability, multi-criteria analysis, new reclaimed areas, soil parameters

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Authors: Nalini Murugaiyah

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Indigenous students require a positive school environment where meaningful learning ought to be there to minimise myriad challenges. Therefore, Orang Asli student’s school environment should be culturally responsive and equipped with student-centred activities or provide constructively designed curriculum and pedagogy. This study sought to extend the knowledge of culturally responsive school leadership practises which relevant and responsive to Orang Asli students through th lens of a theoretical framework, Culturally Responsive School Leadership. The aim of the proposed study is to examine and understand the real-world application of leadership practices that are relevant and responsive to Orang Asli students in Malaysia. This study will also include the often-voiceless voices’ of Orang Asli students, parents, and community leaders to gain a deeper understanding of the process and experience of engaging in culturally responsive school leadership. The study will explore the differences between school leaders, teachers, parents, and community leaders in relation to culturally responsive school environment, non-Orang Asli school leaders’ and teachers’ support to the needs of Orang Asli children, children’s perspectives of teachers’ practices in the classroom align with their culture; and, the demonstration of teacher’s culturally responsive behaviour in the classroom. A basic qualitative study is the proposed research design for this study, and the data is collected through semi-structured interviews and focus group interviews. This qualitative research is designed to gain in-depth knowledge about how the principal’s leadership is culturally responsive towards the school environment, which will improve the quality of education received by the Orang Asli community in Malaysia, hence reducing the drop-out rates in Orang Asli students.

Keywords: indigenous leadership, equity, inclusion, policy

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Authors: J. E. O. Hernandez

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In the next 20 years, energy production by burning fuels will increase and so will the atmospheric concentration of CO2 and its well-known threats to life on Earth. The technologies available for capturing CO2 are still dubious and this keeps fostering an interest in bio-inspired approaches. The leading one is the application of carbonic anhydrase (CA) –a superfast biocatalyst able to convert up to one million molecules of CO2 into carbonates in water. However, natural CA underperforms when applied to real smoky CO2 in chimneys and, so far, the efforts to create superior CAs in the lab rely on screening methods running under pristine conditions at the micro level, which are far from resembling those in chimneys. For the evolution of man-made enzymes, selection rather than screening would be ideal but this is challenging because of the need for a suitable artificial environment that is also sustainable for our society. Herein we present the stepwise design and construction of a bioprocess (from bench-scale to semi-pilot) for evolutionary selection experiments. In this bioprocess, reaction and adsorption took place simultaneously at atmospheric pressure in a spray tower. The scrubbing solution was fed countercurrently by reusing municipal pressure and it was mainly prepared with water, carbonic anhydrase and calcium chloride. This bioprocess allowed for the enzymatic carbonation of smoky CO2; the reuse of process water and the recovery of solid carbonates without cooling of smoke, pretreatments, solvent amines and compression of CO2. The average yield of solid carbonates was 0.54 g min-1 or 12-fold the amount produced in serum bottles at lab bench scale. This bioprocess could be used as a tailor-made environment for driving the selection of superior CAs. The bioprocess and its match CA could be sustainably used to reduce global warming by CO2 emissions from exhausts.

Keywords: biological carbon capture and sequestration, carbonic anhydrase, directed evolution, global warming

Procedia PDF Downloads 180

Authors: Hao-Su Liu, Jun-Qing Lei

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This study introduces the theory of modified particle swarm optimizer and its application in time-domain expressions for bridge self-excited aerodynamic forces. Based on the indicial function expression and the rational function expression in time-domain expression for bridge self-excited aerodynamic forces, the characteristics of the two methods, i.e. the modified particle swarm optimizer and conventional search method, are compared in flutter derivatives’ fitting process. Theoretical analysis and numerical results indicate that adopting whether the indicial function expression or the rational function expression, the fitting flutter derivatives obtained by modified particle swarm optimizer have better goodness of fit with ones obtained from experiment. As to the flutter derivatives which have higher nonlinearity, the self-excited aerodynamic forces, using the flutter derivatives obtained through modified particle swarm optimizer fitting process, are much closer to the ones simulated by the experimental. The modified particle swarm optimizer was used to recognize the parameters of time-domain expressions for flutter derivatives of an actual long-span highway-railway truss bridge with double decks at the wind attack angle of 0°, -3° and +3°. It was found that this method could solve the bounded problems of attenuation coefficient effectively in conventional search method, and had the ability of searching in unboundedly area. Accordingly, this study provides a method for engineering industry to frequently and efficiently obtain the time-domain expressions for bridge self-excited aerodynamic forces.

Keywords: time-domain expressions, bridge self-excited aerodynamic forces, modified particle swarm optimizer, long-span highway-railway truss bridge

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Authors: E. Kempen, M. J. Labuschagne, M. P. Jama

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There is evidence that any learning experience should happen in a safe learning environment as students then will interact, experiment, and construct new knowledge. However, little is known about the specific elements required to create a safe learning environment for the millennial generation, especially in optometry education. This study aimed to identify the specific elements that will contribute to a safe learning environment for the millennial generation of optometry students. Methods: An intrinsic qualitative case study was undertaken with undergraduate students from the Department of Optometry at the University of the Free State, South Africa. An open-ended questionnaire survey was completed after the application of nine different teaching-learning methods based on the experiential learning cycle. A total number of 307 questionnaires were analyzed. Two focus group interviews were also conducted to provide additional data to supplement the data and ensure the triangulation of data. Results: Important elements based on the opinions, feelings, and perceptions of student respondents were analyzed. Students feel safe in an environment with which they are familiar, and when they are familiar with each other, the educators, and the surroundings. Small-group learning also creates a safe and familiar environment. Both these elements create an environment where they feel safe to ask questions. Students value an environment where they are able to learn without influencing their marks or disadvantaging the patients. They enjoy learning from their peers, but also need personal contact with educators. Elements such as consistency and an achievable objective also were also analyzed. Conclusion: The findings suggest that to respond to the real need of this generation of students, insight must be gained in students’ perceptions to identify their needs and the learning environment to optimize learning pedagogies. With the implementation of these personalized elements, optometry students will be able to take responsibility and accountability for their learning.

Keywords: experiences and perceptions, safe learning environment, millennial generation, recommendation for optometry education

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Authors: Hu Zhenxing, Gao Jianxin

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Stereo-based digital image correlation (also referred to as three-dimensional (3D) digital image correlation (DIC)) is a technique for both 3D shape and surface deformation measurement of a component, which has found increasing applications in academia and industries. The accuracy of the reconstructed coordinate depends on many factors such as configuration of the setup, stereo-matching, distortion, etc. Most of these factors have been investigated in literature. For instance, the configuration of a binocular vision system determines the systematic errors. The stereo-matching errors depend on the speckle quality and the matching algorithm, which can only be controlled in a limited range. And the distortion is non-linear particularly in a complex imaging acquisition system. Thus, the distortion correction should be carefully considered. Moreover, the distortion function is difficult to formulate in a complex imaging acquisition system using conventional models in such cases where microscopes and other complex lenses are involved. The errors of the distortion correction will propagate to the reconstructed 3D coordinates. To address the problem, an accurate mapping method based on 2D B-spline functions is proposed in this study. The mapping functions are used to convert the distorted coordinates into an ideal plane without distortions. This approach is suitable for any image acquisition distortion models. It is used as a prior process to convert the distorted coordinate to an ideal position, which enables the camera to conform to the pin-hole model. A procedure of this approach is presented for stereo-based DIC. Using 3D speckle image generation, numerical simulations were carried out to compare the accuracy of both the conventional method and the proposed approach.

Keywords: distortion, stereo-based digital image correlation, b-spline, 3D, 2D

Procedia PDF Downloads 481

Authors: Rozalina Keremedchieva, Ivan Svinyarov, Milen G. Bogdanov

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In continuation of a research project on the application of ionic liquids (ILs) as an alternative to the conventional organic solvents used in the recovery of value added chemicals of industrial interest1-3 we developed a procedure for back extraction and isolation in pure form of the biologically active alkaloid glaucine from IL-based aqueous solutions. One of the approaches applied was the formation of two-phase systems (IL-ATPS) by the addition of kosmotropic salts to the plant extract. The ability of the salts (Na2CO3, MgSO4, (NH4)2SO4, NaH2PO4) to induce the formation of two-phase systems and the influence of pH value on the partition coefficients of glaucine was comprehensively studied. As a result, it was found that the target alkaloid is preferably partitioned into the IL-rich phase regardless of the pH value of the medium and thus shows the inapplicability of the approach used for the isolation of the target compound from the ionic liquid. However, the results obtained can be used as a platform for the development of an analytical method for the quantitative determination of low concentrations of glaucine in biological samples. We further examined the ability of a series of organic solvents such as diethyl ether, Tert-butylmethyl ether, ethyl acetate, butyl acetate, toluene, chloroform, dichloromethane to recover glaucine form raw IL-based aqueous extracts. Optimal conditions for quantitative extraction of glaucine into chloroform were found from which, after removal of the solvent and subsequent recrystallization from ethanol, the target compound was isolated in a high purity as a hydrobromide salt – The form in which it entrance as an active ingredient in various medicines.

Keywords: natural products, ionic liquids, solid-liquid extraction, liquid-liquid extraction

Procedia PDF Downloads 456

Authors: Vinh Duy Cao, Shima Pilehvar, Anna M. Szczotok, Anna-Lena Kjøniksen

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The total energy consumption is dramatically increasing on over the world, especially for building energy consumption where a significant proportion of energy is used for heating and cooling purposes. One of the solutions to reduce the energy consumption for the building is to improve construction techniques and enhance material technology. Recently, microcapsulated phase change materials (MPCM) with high energy storage capacity within the phase transition temperature of the materials is a potential method to conserve and save energy. A new composite materials with high energy storage capacity by mixing MPCM into concrete for passive building technology is the promising candidate to reduce the energy consumption. One of the most untilized building materials for mixing with MPCM is Portland cement concrete. However, the emission of carbon dioxide (CO2) due to producing cement which plays the important role in the global warming is the main drawback of PCC. Accordingly, an environmentally friendly building material, geopolymer, which is synthesized by the reaction between the industrial waste material (aluminosilicate) and a strong alkali activator, is a potential materials to mixing with MPCM. Especially, the effect of MPCM on the thermal and mechanical properties of geopolymer concrete (GPC) is very limited. In this study, high thermal energy storage capacity materials were fabricated by mixing MPCM into geopolymer concrete. This article would investigate the effect of MPCM concentration on thermal and mechanical properties of GPC. The target is to balance the effect of MPCM on improving the thermal performance and maintaining the compressive strength of the geopolymer concrete at an acceptable level for building application.

Keywords: microencapsulated phase change materials, geopolymer concrete, energy storage capacity, thermal performance

Procedia PDF Downloads 288

Authors: Ankit Patil, Tushar D. Deshpande, Yogesh M. Nimdeo

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Pickering emulsions (PE) were developed in response to increased demand for organic, eco-friendly, and biocompatible products. These emulsions are usually stabilized by solid particles. In this research, we created chitosan-based sunflower oil-in-water (O/W) PE without the need for a surfactant. In our work, we employed chitosan, a biopolymer derived from chitin, as a stabilizer. This decision was influenced by chitosan's biocompatibility and biodegradability, as well as its anti-inflammatory and antibacterial capabilities. It also has other functional properties, such as antioxidant activity, a probiotic delivery mechanism, and the ability to encapsulate bioactive compounds. The purpose of this study was to govern key parameters that can be changed to obtain stable PE, such as the concentration of chitosan (0.3-0.5 wt.%), the concentration of oil (0.8-1 vol%), the pH of the emulsion (3-7) manipulated by the addition of 1M HCl/ 4M NaOH, and the amount of electrolyte (NaCl-0-300mM) added to increase or decrease ionic strength. A careful combination of these properties resulted in the production of the most stable and optimal PE. Particle size study found that emulsions with pH 6, 0.4% chitosan, and 300 mM salts were exceptionally stable, with droplet size 886 nm, PI of 0.1702, and zeta potential of 32.753.83 mV. It is fair to infer that when ionic strength rises, particle size, zeta potential, and PI value decrease. A lower PI value suggests that emulsion nanoparticles are more homogeneous. The addition of sodium chloride increases the ionic strength of the emulsion, facilitating the formation of more compact and ordered particle layers. These findings provide light on the creation of stimulus-responsive chitosan-based PE capable of encapsulating bioactive materials, functioning as antioxidants, and serving as food-grade emulsifiers.

Keywords: pickering emulsion, biocompatibility, eco-friendly, chitosan

Procedia PDF Downloads 217

Authors: Mostafa Fanaei, Shahram R. Sistani, Athare Nazri-Panjaki

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Introduction: Critical thinking skills are increasingly recognized as vital for academic success, particularly in higher education. This study examines the influence of critical thinking on learning achievement among undergraduate and master's students enrolled in foreign language programs. By investigating this correlation, educators can gain valuable insights into optimizing teaching methodologies and enhancing academic outcomes. Methods: This cross-sectional study involved 150 students from the Shahid Bahonar University of Kerman, recruited via random sampling. Participants completed the Critical Thinking Questionnaire (CThQ), assessing dimensions such as analysis, evaluation, creation, remembering, understanding, and application. Academic performance was measured using the students' GPA (0-20). Results: The participants' mean age was 21.46 ± 5.2 years, with 62.15% being female. The mean scores for critical thinking subscales were as follows: Analyzing (13.2 ± 3.5), Evaluating (12.8 ± 3.4), Creating (18.6 ± 4.8), Remembering (9.4 ± 2.1), Understanding (12.9 ± 3.3), and Applying (12.5 ± 3.2). The overall critical thinking score was 79.4 ± 18.1, and the average GPA was 15.7 ± 2.4. Significant positive correlations were found between GPA and several critical thinking subscales: Analyzing (r = 0.45, p = 0.013), Creating (r = 0.52, p < 0.001), Remembering (r = 0.29, p = 0.021), Understanding (r = 0.41, p = 0.002), and the overall CThQ score (r = 0.54, p = 0.043). Conclusion: The study demonstrates a significant positive relationship between critical thinking skills and learning achievement in foreign language programs. Enhancing critical thinking skills through educational interventions could potentially improve academic performance. Further research is recommended to explore the underlying mechanisms and long-term impacts of critical thinking on academic success.

Keywords: critical thinking, learning achievement, higher education, foreign language programs, student success

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Authors: Andy Zhang, Awnik Roy, Trevor B. Chen, Bibik Oleksandar, Subodh Adhikari, Paul S. Hsu

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The durability of a combustor in gas-turbine engines is a strong function of its component temperatures and requires good control of these temperatures. Since the temperature of combustion gases frequently exceeds the melting point of the combustion liner walls, an efficient air-cooling system with optimized flow rates of cooling air is significantly important to elongate the lifetime of liner walls. To determine the effectiveness of the air-cooling system, accurate two-dimensional (2D) surface temperature measurement of combustor liner walls is crucial for advanced engine development. Traditional diagnostic techniques for temperature measurement in this application include the rmocouples, thermal wall paints, pyrometry, and phosphors. They have shown some disadvantages, including being intrusive and affecting local flame/flow dynamics, potential flame quenching, and physical damages to instrumentation due to harsh environments inside the combustor and strong optical interference from strong combustion emission in UV-Mid IR wavelength. To overcome these drawbacks, a compact and small borescope long-wave-infrared (LWIR) sensor is developed to achieve 2D high-spatial resolution, high-fidelity thermal imaging of 2D surface temperature in gas-turbine engines, providing the desired engine component temperature distribution. The compactLWIRborescope sensor makes it feasible to promote the durability of a combustor in gas-turbine engines and, furthermore, to develop more advanced gas-turbine engines.

Keywords: borescope, engine, low-wave-infrared, sensor

Procedia PDF Downloads 104